[Chi-square test of homogeneity in clinical studies: A tool for analyzing differences between treatments].

This article explores the application of the chi-squared test of homogeneity in the context of clinical studies, using a previous study on the efficacy of two analgesics for treating headache as an example. The sample included 215 patients, whose responses to treatment were assessed and recorded across four pain intensity categories. The test allowed for the identification of significant differences between the treatments evaluated, proving to be a valuable statistical tool for comparing groups in clinical research.

Implementation of Distance-Based Simulation Training Programs for Healthcare Professionals: Breaking Barriers During COVID-19 Pandemic.

The sudden rise of critically ill patients secondary to the SARS-CoV-2 pandemic has triggered a surge in healthcare response. This project's goal was to provide essential cognitive and technical skills to healthcare professionals returning to the workforce or reassigned to critical care clinical duties during the COVID-19 pandemic. The plan included the implementation of 4 distance-based simulation training programs, with asynchronous personalized feedback.

C-doped anatase TiO: Adsorption kinetics and photocatalytic degradation of methylene blue and phenol, and correlations with DFT estimations.

This work shows an easy and eco-friendly methodology to obtain almost pristine anatase phase of TiO by using furfural, a biomass-derived molecule, as a bio-template. The photocatalytic activity was studied following the degradation of methylene blue and phenol under artificial solar irradiation. Results were compared against those obtained on a commercial pristine anatase TiO.

Electroencephalographic Biomarkers for Treatment Response Prediction in Major Depressive Illness: A Meta-Analysis.

Objective: Reducing unsuccessful treatment trials could improve depression treatment. Quantitative EEG (QEEG) may predict treatment response and is being commercially marketed for this purpose. The authors sought to quantify the reliability of QEEG for response prediction in depressive illness and to identify methodological limitations of the available evidence.